Mark Zuckerberg sat down on the No Priors podcast alongside Priscilla Chan and CZ Biohub’s new AI lead Alex Rives to discuss the organization’s $500 million virtual biology initiative.
Reflecting on the early days of the Chan Zuckerberg Initiative, Zuckerberg recalled that many scientists were openly skeptical of the project’s ambitions.
“We had a series of hilarious meetings with scientists that, like famous Nobel Prize-winning scientists, were just laughing at us,” Priscilla Chan said.
Zuckerberg explained that the goal was never for CZI itself to discover cures. Instead, the organization focused on creating tools that could accelerate research across the broader scientific community.
“To be clear, we don’t think that we’re going to be the ones curing the diseases,” he said. “Our goal was always to build tools that could accelerate the whole scientific field. That way, the scientific field collectively could cure all the diseases.”
He also revealed that his expectations for the pace of progress have changed dramatically over time.
“I thought that by the end of the century was a stretch,” Zuckerberg said. “Now, I think it’s too conservative.”
Discussing the decision to make many of the initiative’s tools open source, Zuckerberg argued that scientific advancement depends on enabling more researchers to contribute.
“We’ll have a bigger impact by getting this in more scientist hands quicker by doing it as open source projects instead,” he said. He added that progress requires more than simply generating data at scale.
“It’s not just like there’s some factory somewhere that you can pay to produce the data,” Zuckerberg explained. “You actually need to invent new novel scientific approaches.”
Returning to the core mission, he emphasized that the initiative’s value lies in helping the entire field move faster rather than directly producing treatments itself.
“The theory isn’t that we’re going to cure the diseases. We’re not,” Zuckerberg said. “It’s that we want to help accelerate the pace of progress for the whole scientific field.”
The discussion then shifted toward a future of highly personalized medicine. Rather than treating diseases with one-size-fits-all solutions, Priscilla Chan described a vision where treatments are designed around an individual’s unique biology.
“I want to understand the genetics of this person,” she said. “I want to understand the risks they have to different illnesses. I want to understand the mechanistic connection between, say, a gene variant, a protein, and a disease process. Because if you understand that through chain, then you can design a protein, design a d**g, bespoke to them, and actually make an intervention.”
Summarizing that vision, Priscilla Chan added: “My goal is to be able to treat the individual as an individual, understand the mechanisms, and be able to intervene.”
Rives also outlined the scale of the work already completed by the team. “We folded over 1.1 billion proteins and predicted their structures,” he said.
According to Rives, one of the most surprising outcomes was that the system developed useful capabilities beyond what it was originally designed to do.
“We didn’t design a model for antibodies,” he said. “We didn’t design a model to be able to bind one particular target. We just designed a model that could understand proteins.”
As a result, he explained, protein design emerged as an unexpected capability of the model rather than a feature that had been deliberately engineered from the start.
Despite the rapid advances in AI, Zuckerberg pushed back against the idea that scientific progress will ultimately be driven by a single all-knowing system.
“Our vision is not that there’s going to be like some central super intelligence that solves all of science,” he said. “I think people are really important and I think we’ll be more important in the future.”
